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lemonfree002
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bert-finetuned-ner

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  1. README.md +12 -12
  2. runs/Sep09_21-36-40_d1b3d82733cd/events.out.tfevents.1725917805.d1b3d82733cd.307.0 +2 -2
README.md CHANGED
@@ -26,16 +26,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9282422646477946
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  - name: Recall
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  type: recall
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- value: 0.9491753618310333
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  - name: F1
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  type: f1
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- value: 0.9385921118322517
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  - name: Accuracy
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  type: accuracy
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- value: 0.9860775887443339
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0606
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- - Precision: 0.9282
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- - Recall: 0.9492
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- - F1: 0.9386
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- - Accuracy: 0.9861
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0776 | 1.0 | 1756 | 0.0661 | 0.8959 | 0.9312 | 0.9132 | 0.9813 |
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- | 0.0343 | 2.0 | 3512 | 0.0644 | 0.9280 | 0.9451 | 0.9365 | 0.9852 |
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- | 0.0202 | 3.0 | 5268 | 0.0606 | 0.9282 | 0.9492 | 0.9386 | 0.9861 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9328493647912885
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  - name: Recall
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  type: recall
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+ value: 0.9515314708852238
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  - name: F1
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  type: f1
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+ value: 0.942097808881113
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9867398598928593
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0587
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+ - Precision: 0.9328
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+ - Recall: 0.9515
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+ - F1: 0.9421
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+ - Accuracy: 0.9867
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.077 | 1.0 | 1756 | 0.0651 | 0.9058 | 0.9350 | 0.9202 | 0.9815 |
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+ | 0.0347 | 2.0 | 3512 | 0.0612 | 0.9281 | 0.9475 | 0.9377 | 0.9856 |
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+ | 0.0206 | 3.0 | 5268 | 0.0587 | 0.9328 | 0.9515 | 0.9421 | 0.9867 |
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  ### Framework versions
runs/Sep09_21-36-40_d1b3d82733cd/events.out.tfevents.1725917805.d1b3d82733cd.307.0 CHANGED
@@ -1,3 +1,3 @@
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